
Bewitch
Romantic AI companion for immersive roleplay conversations.
What it does
Most AI companion apps either feel robotic or jump straight into explicit content. Bewitch focuses on romantic tension, immersive roleplay, and conversations that evolve naturally over time, the space in between. Available in 5 languages, with both curated characters and fully customizable AI personas. Built for people looking for emotional immersion, not just another chatbot.
Does the same job
all alternatives →- WLWhisperFusion – Low-latency conversations with an AI chatbot2024 · github.com · ▲272
WhisperFusion builds upon the capabilities of open source tools WhisperLive and WhisperSpeech to provide a seamless conversations with an AI chatbot.



- BTBe the ChatBOTJul 2026 · bethechatbot.com · ▲55
I made this experimental art project/game that's an LLM chat assistant, but where you're the AI. I wanted people to get a visceral sense of what it's like to answer the kinds of things that people prompt their chatbots day in and day out. If you're interested, I wrote up some more info on how I made it, including how the "user" prompts are generated with an eye for realism: https://bethechatbot.com/about Hope you enjoy it! I'd love to hear people's takeaways.
- RFRoleplay-first chat UI for an OpenAI-compatible chat completions APIJan 2026 · abliteration.ai · ▲10
I built a dedicated roleplay chat UI for abliteration.ai: https://abliteration.ai/roleplay The backend is OpenAI-compatible (/v1/chat/completions), with usage-based pricing and no prompt/output retention by default (details on the site). The UI is meant for long-form character chats and interactive fiction, without needing a local frontend. Docs (including a roleplay backend guide and a SillyTavern integration guide): https://abliteration.ai/docs Would love feedback on missing RP features, UX rough edges, and what you would expect from a…
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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